Shulou(Shulou.com)06/03 Report--

As a program developer in the era of Ai artificial intelligence, no matter whether you are involved in the technical development of big data and artificial intelligence, you need to know some commonly used machine learning algorithms. Today, the wax torch education teacher will recommend 10 necessary algorithms for you.

1. Linear regression: in the field of statistics and machine learning, linear regression is the most widely used and easiest algorithm to get started.

2. Logistic regression: Logistic regression is a technique borrowed from the field of statistics, which mainly deals with the problem of binary classification.

3. Linear discriminant analysis: linear discriminant analysis algorithm (LDA) is the preferred classification technique to deal with more than two kinds of problems.

4. Classification and regression tree: decision tree is an important prediction modeling algorithm, its learning speed is very fast, and the speed of making prediction is also very fast.

5. Naive Bayes: naive Bayes is a simple and effective predictive modeling algorithm, which assumes that each input variable is independent of each other. This algorithm works very well when dealing with a large number of complex problems.

6. K-nearest neighbor algorithm: the K-nearest neighbor (KNN) algorithm is very simple. The KNN model represents the entire training data set. Sometimes, KNN needs a lot of memory or space to store all the data, but the calculation is performed only when prediction is needed.

7. Learning vector quantization: different from KNN, learning vector quantization algorithm (LVQ) can select the required training instance data and learn these instances accurately, without the need to deal with the whole training data set.

8. Support vector machine: support vector machine (SVM) is one of the most powerful classifiers that can be directly used in the field of machine learning.

9. Bagging and random forest: random forest is an integrated machine learning algorithm, which is widely used in the field of machine learning.

10. Boosting and AdaBoost:Boosting are an integrated technique that attempts to take advantage of a large number of weak classifiers; AdaBoost is the first real Boosting algorithm developed for binary classification problems.

As the most commonly used algorithms in the industry, the above 10 machine learning algorithms have a very important position. It is suggested that every programmer should have a simple or in-depth understanding, and it is best to apply them to actual business scenarios.

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